Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17CB2723C310624A77173D9E3B30D3529B2B1B564DBB3F6C8E7E192384AD9CD94B64A18 |
|
CONTENT
ssdeep
|
768:4fxe0P+CIUoFe/13odaW7mnpi5J+xrVQ7bmt:RDUJ+EYOt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eded139212ec4c96 |
|
VISUAL
aHash
|
ffd1f1d1ffffe700 |
|
VISUAL
dHash
|
388323b32c274c60 |
|
VISUAL
wHash
|
ffc1c1c1dfff0000 |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
28132323b32c274c,070fc9c5d5b589b2,0529968eac940801,40104c6169165454 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 262 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
| ID | Portugués | Inglés | Trigger |
|---|---|---|---|
Pages with identical visual appearance (based on perceptual hash)